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by Avigdor Gal
Download Uncertain Schema Matching (Synthesis Lectures on Data Management) fb2
Networking & Cloud Computing
  • Author:
    Avigdor Gal
  • ISBN:
    1608454339
  • ISBN13:
    978-1608454334
  • Genre:
  • Publisher:
    Morgan & Claypool Publishers; 1 edition (March 1, 2011)
  • Pages:
    100 pages
  • Subcategory:
    Networking & Cloud Computing
  • Language:
  • FB2 format
    1959 kb
  • ePUB format
    1721 kb
  • DJVU format
    1428 kb
  • Rating:
    4.2
  • Votes:
    661
  • Formats:
    lit lrf azw doc


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Электронная книга "Uncertain Schema Matching", Avigdor Gal. Эту книгу можно прочитать в Google Play Книгах на компьютере, а также на устройствах Android и iOS. Выделяйте текст, добавляйте закладки и делайте заметки, скачав книгу "Uncer. Выделяйте текст, добавляйте закладки и делайте заметки, скачав книгу "Uncertain Schema Matching" для чтения в офлайн-режиме. A Gal. Synthesis Lectures on Data Management 3 (1), 1-97, 2011. Why is schema matching tough and what can we do about it? A Gal. Sigmod Record 35 (4), 2-5, 2006. Heterogeneous Stream Processing and Crowdsourcing for Urban Traffic Management. A Artikis, M Weidlich, F Schnitzler, I Boutsis, T Liebig, N Piatkowski,. EDBT 14, 712-723, 2014.

TAGS Data Management, Morgan & Claypool Publishers, Uncertain Schema Matching, Claypool Publishers, Synthesis Lectures.

Synthesis Lectures on Data Management : Uncertain Schema Matching. San Rafael, CA, USA: Morgan & Claypool Publishers, 2011. Morgan & Claypool Publishers. May not be reproduced in any form without permission from the publisher, except fair uses permitted under . TAGS Data Management, Morgan & Claypool Publishers, Uncertain Schema Matching, Claypool Publishers, Synthesis Lectures. Our approach toward this book was to conceptualize data cleaning solutions as being com-posed of tasks and operators.

e series will publish 50- to 125 page publications on topics pertaining to data management. Uncertain Schema Matching. Fundamentals of Object Databases: Object-Oriented and Object-Relational Design.

Gal, . Synthesis Lectures on Data Management. Morgan & Claypool Publishers, San Rafael (2011)Google Scholar.

Schema matching is used for data integration, mediation, and conversion between heterogeneous sources. Nevertheless, mappings identified with an automatic or semi-automatic process can never be completely certain. In a process of concept alignment, it is necessary to manage uncertainty. In this paper, we present a fuzzy-based process of concept alignment for uncertainty management in schema matching problem. The ultimate goal is to enable interoperability between different electronic health records

Uncertain Schema Matching. Avigdor Gal. Published: 28 February 2011. by Morgan & Claypool Publishers LLC. in Synthesis Lectures on Data Management. Synthesis Lectures on Data Management, Volume 3, pp 1-97; doi:10. Keywords: Uncertain Schema Matching. Cited by 19 articles. For questions or feedback, please reach us at support at scilit

Avigdor Gal: Uncertain Schema Matching. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2011.

Avigdor Gal: Uncertain Schema Matching. load citations from opencitations. net to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data.

Schema matching is the task of providing correspondences between concepts describing the meaning of data in various heterogeneous, distributed data sources. Schema matching is one of the basic operations required by the process of data and schema integration, and thus has a great effect on its outcomes, whether these involve targeted content delivery, view integration, database integration, query rewriting over heterogeneous sources, duplicate data elimination, or automatic streamlining of workflow activities that involve heterogeneous data sources. Although schema matching research has been ongoing for over 25 years, more recently a realization has emerged that schema matchers are inherently uncertain. Since 2003, work on the uncertainty in schema matching has picked up, along with research on uncertainty in other areas of data management. This lecture presents various aspects of uncertainty in schema matching within a single unified framework. We introduce basic formulations of uncertainty and provide several alternative representations of schema matching uncertainty. Then, we cover two common methods that have been proposed to deal with uncertainty in schema matching, namely ensembles, and top-K matchings, and analyze them in this context. We conclude with a set of real-world applications. Table of Contents: Introduction / Models of Uncertainty / Modeling Uncertain Schema Matching / Schema Matcher Ensembles / Top-K Schema Matchings / Applications / Conclusions and Future Work